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2008/09 Undergraduate Module Catalogue

MATH1351 Applications of Mathematics

10 creditsClass Size: 250

Module manager: Dr J. Niesen
Email: jitse@maths.leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2008/09

Pre-requisite qualifications

A good A-level Mathematics grade or equivalent.

This module is approved as an Elective

Module summary

The first part of this module introduces vectors as a powerful tool for solving geometric and kinematic problems in 2 and 3 dimensions. The second part introduces the concept of discrete (as opposed to continuous) rates of change and uses this to model simple systems that arise in numerical calculation, biology, finance and economics.

Objectives

To Introduce a variety of stimulating applications of mathematics and to formulate important classes of such problems in order to establish the foundations of modelling for subsequent applied modules. To acquaint students with some essential tools for solving problems in applied mathematics. By the end of this module, students should be able to: a) understand vector algebra and be able to apply vectors to diverse problems involving lines and planes in 2 and 3 dimensions; b) differentiate and integrate time-dependent vectors and apply this to kinematics in 2 and 3 dimensions; c) distinguish between continuous and discrete processes; d) derive and solve difference equations describing simple discrete processes.

Syllabus

a) Vectors: vector algebra, (addition, linear independence, components, scalar and vector multiplication, triple products). Geometry of lines and planes. Time-dependent vectors (differentiation and integration). Kinematics of particles in 2 and 3 dimensions. b) Discrete systems: Quantization of time increments, rates of change, discrete models, iteration, difference equations. Linear first order difference equations (general solutions, fixed points, stability). Non-linear first order difference equations (fixed points, cobweb diagrams, stability, cycles). Second order linear difference equations (general solutions, fixed points, stability). Applications to numerical algorithms, biology, finance (e.g. mortgages etc.) and economics. One dimensional logistic equations (period doubling).

Teaching methods

Delivery typeNumberLength hoursStudent hours
Lecture221.0022.00
Tutorial111.0011.00
Private study hours67.00
Total Contact hours33.00
Total hours (100hr per 10 credits)100.00

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
In-course Assessment.15.00
Total percentage (Assessment Coursework)15.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 00 mins85.00
Total percentage (Assessment Exams)85.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 08/07/2008

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